Young Researcher Paper Award 2023
🥇Winners

Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 31, Number 6(1) (2019)
Copyright(C) MYU K.K.
pp. 1847-1869
S&M1903 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2019.2308
Published: June 7, 2019

Recognizing Falls, Daily Activities, and Health Monitoring by Smart Devices [PDF]

Sittichai Sukreep, Khalid Elgazzar, Cheehung Henry Chu, Chakarida Nukoolkit, and Pornchai Mongkolnam

(Received January 21, 2019; Accepted March 25, 2019)

Keywords: health monitoring, smart devices, IoT, daily activity, fall recognition, data mining, classification

One of the biggest challenges in ageing societies is to improve life, health, safety, and support of the elderly population in their daily life. Currently, the number of elderly people living alone is increasing every year. Living alone allows more freedom but raises the risk of serious injuries or fatal accidents. Falls are the key cause of significant health problems, especially for an elderly person who lives alone. Moreover, vital signs such as heart rate, balancing activities, and environmental context are crucial in relation to the user’s condition. To assist people living alone and improve their health quality, we firmly believe that the advances in Smart Devices, Smart Environment, and Internet of Things paradigms are very helpful for developing a fall and activity recognition system. We propose a system using an unobtrusive device consisting of a smartwatch and a smartphone to identify falls and thirteen daily activities (e.g., walking, running, typing, and waving the hand). The events leading to a fall, the speed of falling down, the heart rate while doing an activity, and the time passed since the fall are important data that we store to help a doctor diagnose and rehabilitate a patient. Environment sensors are used to indicate the indices of ambient conditions such as temperature, humidity, brightness, and motion detected. Suitable machine learning techniques are used for daily activity recognition, and the processing time for classification was compared on the basis of a smartwatch and an Amazon Web Services (AWS) cloud server. Threshold-based health risk analysis models are utilized for abnormal activity recognition and heart rate and heat index (temperature and humidity) determination. The system issues different types of notifications such as warning messages, sounding alarms, and phone calls to related persons such as family members, caregivers, or doctors. Various easy-to-understand visualizations are presented to track and monitor the subjects in real time, including heart rate, daily activity summary, health risk status, and environmental information.

Corresponding author: Sittichai Sukreep


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Sittichai Sukreep, Khalid Elgazzar, Cheehung Henry Chu, Chakarida Nukoolkit, and Pornchai Mongkolnam, Recognizing Falls, Daily Activities, and Health Monitoring by Smart Devices, Sens. Mater., Vol. 31, No. 6, 2019, p. 1847-1869.



Forthcoming Regular Issues


Forthcoming Special Issues

Special Issue on Applications of Novel Sensors and Related Technologies for Internet of Things
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
Call for paper


Special Issue on Advanced Sensing Technologies for Green Energy
Guest editor, Yong Zhu (Griffith University)
Call for paper


Special Issue on Room-temperature-operation Solid-state Radiation Detectors
Guest editor, Toru Aoki (Shizuoka University)
Call for paper


Special Issue on International Conference on Biosensors, Bioelectronics, Biomedical Devices, BioMEMS/NEMS and Applications 2023 (Bio4Apps 2023)
Guest editor, Dzung Viet Dao (Griffith University) and Cong Thanh Nguyen (Griffith University)
Conference website
Call for paper


Special Issue on Advanced Sensing Technologies and Their Applications in Human/Animal Activity Recognition and Behavior Understanding
Guest editor, Kaori Fujinami (Tokyo University of Agriculture and Technology)
Call for paper


Special Issue on Signal Collection, Processing, and System Integration in Automation Applications
Guest editor, Hsiung-Cheng Lin (National Chin-Yi University of Technology)
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.